Paper detail

Characterization of high frequency oscillations and EEG frequency spectra using the damped-oscillator oscillator detector (DOOD)

Objective: The surgical resection of brain areas with high rates of visually identified high frequency oscillations (HFOs) on EEG has been correlated with improved seizure control. However, it can be difficult to distinguish normal from pathological HFOs, and the visual detection of HFOs is very time-intensive. An automated algorithm for detecting HFOs and for wide-band spectral analysis is desirable. Methods: The damped-oscillator oscillator detector (DOOD) is adapted for HFO detection, and tested on recordings from one rat and one human. The rat data consist of recordings from the hippocampus just prior to induction of status epilepticus, and again 6 weeks after induction, after the rat is epileptic. The human data are temporal lobe depth electrode recordings from a patient who underwent pre-surgical evaluation. Results: Sensitivities and positive predictive values are presented which depend on specifying a threshold value for HFO detection. Wide-band time-frequency and HFO-associated frequency spectra are also presented. In the rat data, four high frequency bands are identified at 80-250 Hz, 250-500 Hz, 600-900 Hz and 1000-3000 Hz. The human data was low-passed filtered at 1000 Hz and showed HFO-associated bands at 15 Hz, 85 Hz, 400 Hz and 700 Hz. Conclusion: The DOOD algorithm is capable of high resolution time-frequency spectra, and it can be adapted to detect HFOs with high positive predictive value. HFO-associated wide-band data show intricate low-frequency structure. Significance: DOOD may ease the labor intensity of HFO detection. DOOD wide-band analysis may in future help distinguish normal from pathological HFOs.